Method and apparatus for improved metabolite signal separation in MR spectroscopy

ABSTRACT

A technique is set forth for MR spectroscopy that is capable of reducing signal overlap between metabolite signals for improved clinical analysis of metabolite content. The technique includes varying an echo time across a scanning dimension. Once a span of echo time for an acquisition dimension is determined, and the number of acquisition data points is known, a variance between echo times can be determined. A pulse sequence with differing echo times is then applied for each frame, and after data is acquired, an image is reconstructed that significantly improves metabolite signal separation.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation and claims priority of U.S.Ser. No. 10/250,260 filed Jun. 18, 2003, now U.S. Pat. No. 6,987,997.

BACKGROUND OF THE INVENTION

The present invention relates generally to MR spectroscopy, and moreparticularly, to a technique that is capable of segregating metabolitesignals for improved clinical analysis.

When a substance such as human tissue is subjected to a uniform magneticfield (polarizing field B₀), the individual magnetic moments of thespins in the tissue attempt to align with this polarizing field, butprecess about it in random order at their characteristic Larmorfrequency. If the substance, or tissue, is subjected to a magnetic field(excitation field B₁) which is in the x-y plane and which is near theLarmor frequency, the net aligned moment, or “longitudinalmagnetization”, M_(z), may be rotated, or “tipped”, into the x-y planeto produce a net transverse magnetic moment M_(t). A signal is emittedby the excited spins after the excitation signal B₁ is terminated andthis signal may be received and processed to form an image.

When utilizing these signals to produce images, magnetic field gradients(G_(x) G_(y) and G_(z)) are employed. Typically, the region to be imagedis scanned by a sequence of measurement cycles in which these gradientsvary according to the particular localization method being used. Theresulting set of received NMR signals are digitized and processed toreconstruct the image using one of many well known reconstructiontechniques.

The use of nuclear magnetic resonance imaging for the determination ofindividual chemical compounds is known as MR spectroscopy (MRS). Theunderlying principle of MRS is that atomic nuclei are surrounded by acloud of electrons which very slightly shield the nucleus from anyexternal magnetic field. As a structure of the electron cloud isspecific to an individual molecule or compound, the magnitude of thisscreening effect is then also a characteristic of the chemicalenvironment of individual nuclei. In view of the fact that the resonantfrequency is proportional to the magnetic field it experiences, theresonant frequency can be determined not only by the external appliedfield, but also by the small field shift generated by the electroncloud. This shift in frequency is called the chemical shift. It is notedthat the chemical shift is a very small effect and is usually expressedas “parts per million” (PPM) of the main frequency. In order to resolvethe different chemical species, it is therefore necessary to achievevery high levels of homogeneity of the main magnetic field B₀.

In the context of human MRS, two nuclei are of particular interest, H¹and P³¹. Proton MR spectroscopy is mainly employed in studies of thebrain where prominent peaks arise from certain metabolites. Phosphorus31 MR spectroscopy detects compounds involved in energy metabolism incertain compounds related to membrane synthesis and degradation.Metabolites of particular interest in MRS studies include glutamate(Glu), glutamine (Gln), choline (Cho), creatine (Cre), N-acetylaspartate(NAA), and the inositols (ml and sl).

Glu is the principal excitatory neurotransmitter of the central nervoussystem. In brain, Glu, Gln, and Glu/Gln-enzymes are compartmentalizedwithin neurons and glial cells (astrocytes). Transient increases inextracellular Glu (Glu₀) associated with neruotransmission is importantfor normal brain function. From the synaptic space, Glu₀ is recycled andinternalized by glial cells and converted to Gln. This normal cycleprevents glutamate from accumulating in the extracellular compartmentwhere it binds to membrane receptors, such as N-methyl-D-aspartate(NMDA) and ampa-kainate proteins. Prolonged extracellular exposure tohigh Glu₀, however, is toxic. Excess Glu₀ in the synaptic space cantrigger a toxic cascade, via NMDA receptors, leading to neuronal andnon-neuronal (oligodendrocyte) cell death because of excessiveaccumulation of intracellular calcium, which in turn leads to freeradicals and nitric oxide production as well as formation of apoptoticbodies. This neural excitotoxicity cascade might have a key role in anumber of neurodegenerative diseases, including MS, AD, ALS, HD, and asa bystander effect in stroke and brain trauma. Even gliomas have beenfound to respond to glutamate antagonists. Although Glu₀ is probablybelow detectability by whole body 3T MR spectroscopy, intracellularconcentrations of both Glu and Gln are high enough for MRS detection. Inconventional proton spectra, the overlapped signals of Glu and Gln arereadily measured as total Glu+Gln (Glx). Some studies have shownincreases in Glx for severe abnormalities such as hypoxicencephalopathy, acute MS lesions, HD, ALS, and certain tumors. Decreasesin the Glx signal have also been reported. Unfortunately, Glx does notmeasure changes in Glu/Gln status, and is therefore unlikely to be anadequate marker for less profound changes in intracellular conditions,which may proceed or accompany conditions of toxic Glu₀. Spectraloverlap of Gln, Glu, NAA, and ml make it difficult to reliably sort outGlu and Gln individually in conventional spectra.

It would therefore be advantageous to have a technique to provideimproved in vivo spectroscopic measurement of metabolites, such asglutamate, glutamine, choline, creatine, N-acetylaspartate and theinositols.

BRIEF DESCRIPTION OF THE INVENTION

The present invention solves the aforementioned drawbacks in MRspectroscopy of metabolites by varying the echo time across theacquisition dimension so that overlap of various metabolite signals issignificantly reduced. This technique therefore provides improved invivo spectroscopic measurement of metabolites, such as glutamate (Glu),glutamine (Gln), choline (Cho), creatine (Cre), N-acetylaspartate (NAA),and the inositols (ml and sl). In application, the technique providesdirect measurement of Glu and Gln in human brain spectroscopy bysignificantly reducing overlap of the resulting signals from thesemetabolites, as well as from signals from other molecules such as GABA,glutathione, and macro-molecular components.

In accordance with one aspect of the invention, a method of MRspectroscopy is disclosed that reduces signal overlap from metabolites.The technique includes determining a plurality of echo times over a TEaveraged dimension, determining a number of data acquisition points, andvarying an echo time in duration from one data acquisition to anotheracross the TE averaged dimension based on the number of data acquisitionpoints. This technique is effective at detecting spatial distribution ofmetabolite signals to segregate metabolite signals for clinicalanalysis.

In accordance with another aspect of the invention, an apparatus isdisclosed to acquire MR spectroscopy images having metabolitedistinction. The apparatus includes an MRI system having a plurality ofgradient coils positioned about a bore of a magnet to impress apolarizing magnetic field. An RF transceiver system and an RF switch arecontrolled by a pulse module to transmit and receive RF signals to andfrom an RF coil assembly to acquire MR images. The MRI apparatus alsoincludes a computer programmed receive a desired average echo time foran acquisition dimension and a desired number of acquisition points. Avariance from one echo time to another can then be determined. Thissystem then applies a pulse sequence with differing echo times, althoughnot every echo time must be different. Data is acquired in an image thatis reconstructed with improved metabolite signal separation that is dueto the differing echo times.

In accordance with yet another aspect of the invention a computerprogram is disclosed having a set of instructions which, when executedby a computer, causes the computer to apply a pulse sequence having aplurality of data acquisition echo times that are averaged over anacquisition period, wherein at least three echo times are differing inlength. The program also includes instructions to reconstruct an MRimage, the MR image having distinction between various metabolitesignals.

Various other features, objects and advantages of the present inventionwill be made apparent from the following detailed description and thedrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings illustrate one preferred embodiment presently contemplatedfor carrying out the invention.

In the drawings:

FIG. 1 is a schematic block diagram of an MR imaging system for use withthe present invention.

FIG. 2 is a schematic representation of a portion of a pulse sequenceand data acquisition scheme that can be implemented in the system ofFIG. 1 in accordance with one embodiment of the present invention.

FIG. 3 is a graphical representation of several metabolites versusfrequency depicting results from a conventional MR spectroscopyexamination.

FIG. 4 is a graphical representation, similar to that of FIG. 3, showingthe results of the pulse sequence of FIG. 2 implemented in an MRspectroscopy examination.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Referring to FIG. 1, the major components of a preferred magneticresonance imaging (MRI) system 10 incorporating the present inventionare shown. The operation of the system is controlled from an operatorconsole 12 which includes a keyboard or other input device 13, a controlpanel 14, and a display screen 16. The console 12 communicates through alink 18 with a separate computer system 20 that enables an operator tocontrol the production and display of images on the display screen 16.The computer system 20 includes a number of modules which communicatewith each other through a backplane 20 a. These include an imageprocessor module 22, a CPU module 24 and a memory module 26, known inthe art as a frame buffer for storing image data arrays. The computersystem 20 is linked to disk storage 28 and tape drive 30 for storage ofimage data and programs, and communicates with a separate system control32 through a high speed serial link 34. The input device 13 can includea mouse, joystick, keyboard, track ball, touch activated screen, lightwand, voice control, or any similar or equivalent input device, and maybe used for interactive geometry prescription.

The system control 32 includes a set of modules connected together by abackplane 32 a. These include a CPU module 36 and a pulse generatormodule 38 which connects to the operator console 12 through a seriallink 40. It is through link 40 that the system control 32 receivescommands from the operator to indicate the scan sequence that is to beperformed. The pulse generator module 38 operates the system componentsto carry out the desired scan sequence and produces data which indicatesthe timing, strength and shape of the RF pulses produced, and the timingand length of the data acquisition window. The pulse generator module 38connects to a set of gradient amplifiers 42, to indicate the timing andshape of the gradient pulses that are produced during the scan. Thepulse generator module 38 can also receive patient data from aphysiological acquisition controller 44 that receives signals from anumber of different sensors connected to the patient, such as ECGsignals from electrodes attached to the patient. And finally, the pulsegenerator module 38 connects to a scan room interface circuit 46 whichreceives signals from various sensors associated with the condition ofthe patient and the magnet system. It is also through the scan roominterface circuit 46 that a patient positioning system 48 receivescommands to move the patient to the desired position for the scan.

The gradient waveforms produced by the pulse generator module 38 areapplied to the gradient amplifier system 42 having G_(x), G_(y), andG_(z) amplifiers. Each gradient amplifier excites a correspondingphysical gradient coil in a gradient coil assembly generally designated50 to produce the magnetic field gradients used for spatially encodingacquired signals. The gradient coil assembly 50 forms part of a magnetassembly 52 which includes a polarizing magnet 54 and a whole-body RFcoil 56. A transceiver module 58 in the system control 32 producespulses which are amplified by an RF amplifier 60 and coupled to the RFcoil 56 by a transmit/receive switch 62. The resulting signals emittedby the excited nuclei in the patient may be sensed by the same RF coil56 and coupled through the transmit/receive switch 62 to a preamplifier64. The amplified MR signals are demodulated, filtered, and digitized inthe receiver section of the transceiver 58. The transmit/receive switch62 is controlled by a signal from the pulse generator module 38 toelectrically connect the RF amplifier 60 to the coil 56 during thetransmit mode and to connect the preamplifier 64 to the coil 56 duringthe receive mode. The transmit/receive switch 62 can also enable aseparate RF coil (for example, a surface coil) to be used in either thetransmit or receive mode.

The MR signals picked up by the RF coil 56 are digitized by thetransceiver module 58 and transferred to a memory module 66 in thesystem control 32. A scan is complete when an array of raw k-space datahas been acquired in the memory module 66. This raw k-space data isrearranged into separate k-space data arrays for each image to bereconstructed, and each of these is input to an array processor 68 whichoperates to Fourier transform the data into an array of image data. Thisimage data is conveyed through the serial link 34 to the computer system20 where it is stored in memory, such as disk storage 28. In response tocommands received from the operator console 12, this image data may bearchived in long term storage, such as on the tape drive 30, or it maybe further processed by the image processor 22 and conveyed to theoperator console 12 and presented on the display 16.

The present invention includes a method and system suitable for use withthe above-referenced MR system, or any similar or equivalent system forobtaining MR images.

The invention includes a technique that provides improved in vivospectroscopic measurement of metabolites that reduces signal overlap inthe metabolites of interest. In general, the invention includesdetermining a number of different echo times over a TE averageddimension and determining a number of data acquisition points. The echotime (TE) is varied in duration from one data acquisition to anotheracross the TE averaged dimension based on the number of data acquisitionpoints. After acquiring data, the data is then averaged based on thenumber of different echo times. In this manner, a significant reductionin signal overlap from metabolites of interest is achieved in theTE-averaged data, thereby allowing the detection of spatial distributionof metabolite signals to segregate metabolite signals for clinicalanalysis. This technique of TE-averaging can also be accomplished usingan FFT in the TE-averaging dimension and extraction of zero frequencyspectrum.

The invention is implemented in a system such as that described withreference to FIG. 1 wherein the processing computer is programmed toreceive an initial echo time and a desired span of echo time for anacquisition dimension. A desired number of acquisition points isdetermined as well as a variance from one echo time to another. A pulsesequence is then applied with differing echo times to acquire data andreconstruct a spectrum or spectral image with improved metabolite signalseparation. Alternately, the span of echo times used in TE-averaging canbe provided as a listing.

The invention is also implemented in a computer program stored on acomputer readable storage medium that, when executed by a computer,causes the computer to apply a pulse sequence having a number of dataacquisition echo times that are averaged over an acquisition period,wherein at least three of those echo times are different in duration. AnMR image is then reconstructed having distinction between variousmetabolite signals.

In a preferred embodiment, as shown in FIG. 2, a pulse sequence 100 forthree frames 102, 104, and 106 is shown in which a variance from oneecho time (TE) to another is fixed across the acquisition dimension. Theecho times are incremented the fixed variance from a nominal value, suchas that shown in Frame 102, to that of Frame 104, and then to Frame 106,and so on. Each frame sequence includes an excitation RF pulse 108,followed by a set of refocusing RF pulses 110 that includes a firstrefocusing RF pulse 112, which is substantially the same for each frame.The first refocusing RF pulse 112 is played out a time te1 from theexcitation pulse 108 and is followed by a second refocusing RF pulse 114at a time of TE₀/2. This combination of RF pulses generates an echo 116centered at TE₀/ 2−te1 following RF pulse 114. As indicated in theexemplary technique 100, the total echo time of Frame 102, designated asTE₀, is the time from the excitation RF pulse 108 to the echo 116. Thistime is increased, or incremented, by 2Δ in Frame 104 such that thetotal echo time of Frame 104 is TE₀+2Δ, and is incremented by another 2Δfor Frame 106 for a total echo time of TE₀+4Δ. In general then, thetotal echo time for Frame n is TE₀+2(n−1)Δ. As one skilled in the artwill readily recognize, for 3D volume selection, the aforementionedsequence would be accompanied by three mutually orthogonal gradientpulses for each frame. In this case, a double spin echo (PRESS)acquisition scheme is used.

There are many ways to vary the echo times. Incrementing a fixedincrement is just one example and is the current preferred embodiment.Equivalently, the echo times may be varied a non-fixed amount and/or maybe decremented as well. These and other techniques are contemplated andare within the scope of the present invention.

A particular application of the aforementioned spectroscopy technique isfor automated in vivo detection of glutamate (Glu) and glutamine (Gln).As previously described, the signals from Gln and Glu are typicallyseverally overlapped with one another, and with the signals from othermolecules such as NAA, and ml as shown in FIG. 3. The graph of FIG. 3shows the spectra acquired using a conventional acquisition scheme,known as PRESS, having TE of 35, TR of 2000 in a 3T scanner. Typical invivo data 130 is shown on the top of the scale and individual chemicalresponses are depicted below for NAA 132, Glu 134, Gln 136, and ml 138.As indicated in the two areas of interest 140 and 142, severe spectraloverlap occurs across the metabolite signals that make it extremelydifficult to quantify individual metabolite signals. At field strengthsnormally used for clinical MR spectroscopy (1.5T and 3.0T), even priorknowledge fitting programs are forced to fit a sum of Glu+Gln (Glx) todetermine tissue levels. According to recent research on theexcitotoxicity events associated with a shift in Glu:Gln, it would beadvantageous to measure both Glu and Gln, rather than a sum of thesecomponents, commonly referred to as Glx.

Implementing the aforementioned scheme provides for direct measurementof Glu and Gln in human brain spectra at 3T, as shown in FIG. 4. Similarto FIG. 3, FIG. 4 shows various metabolite spectra. Like numerals areused to identify the similar signals. However, as shown in the two areasof interest 144 and 146, with implementation of the present invention,significant signal differentiation is achieved. By incrementing TE froma nominal minimal value of approximately 30 ms., to at least 115 ms., TEaveraging simplifies spectral patterns for NAA 132, Glu 134, Gln 136,and ml 138. As indicated in the areas of interest 144 and 146, the Glusignal acquired in 146 is easily subtracted from that acquired in 144 toprovide a measurement of Gln. It is also contemplated that larger and/ornon-linear steps in the t1 dimension can also be used, especially inconventional MRSI, where sampling time is dominated by k-space encoding.

Using this TE averaged technique with PRESS provides sufficientresolution for improved quantification at 3T and above, for the tissuelevels of various metabolites, specifically, Glu, Gln, ml, NA_(tot),Cho, and Cre. However, given the variation of T2 across a normalpopulation, it may be advantageous to calculate individual T2 from thedata prior to TE-averaging for absolute quantification.

It is also noted that while excellent data was acquired by averaging TEfrom 35 ms. to 335 ms., in 128 steps of 2.5 ms. and NEX of 2, and TR of2 sec., substantially equivalent data was acquired in 64 steps of 2.5ms. averaging TE from 35 ms. to 195 ms., 2 NEX and 2 sec. TR and alsofor example 16 steps of 10 ms, averaging over the same span of TE.

Accordingly, this technique provides optimized spectra for quantitativemeasurement of metabolites providing a good baseline and sufficientresolution at relatively short effective TE values, and with relativelyfew points in t1.

Additionally, to determine metabolite levels independent of T₂variability in any given subject, if prior to TE averaging, T₂relaxation and estimated signal at TE=0 is determined, this data can beused in concert with a standard phantom to provide independentmetabolite levels. Such phantoms include the GE MRS HD phantom from GEMedical Systems, Waukesha, Wis., part/model no. 2152220.

It is also contemplated that each frame of TE data can be phasecorrected using a residual water signal. Additionally, a water referencepoint can be included to correct any frequency and phase errors. Waterreference can also include a TE-averaged frame of unsuppressed data.

The present invention has been described in terms of the preferredembodiment, and it is recognized that equivalents, alternatives, andmodifications, aside from those expressly stated, are possible andwithin the scope of the appending claims.

1. A method of MR spectroscopy to reduce signal overlap from metabolitescomprising the steps of: determining a plurality of echo times (TE) ofdifferent lengths within a single selected data acquisition session;acquiring data during a set of TEs that comprises the plurality of TEsof different lengths within the single selected data acquisitionsession; averaging the data acquired within the single selected dataacquisition session; and detecting spatial distribution of metabolitesignals to segregate metabolite signals for clinical analysis from theaveraged data within the single selected data acquisition session. 2.The method of claim 1 wherein the step of averaging the data acquiredcomprises: determining an initial echo time (TE₀); determining a numberof data acquisition points; varying TE in duration from one dataacquisition to another across the TE averaged dimension based on thenumber of data acquisition points and TE₀; accumulating data acquiredfor the plurality of different TEs; and dividing the accumulated data bythe number of data acquisition points.
 3. The method of claim 1 furthercomprising incrementing TE from one data acquisition to a next.
 4. Themethod of claim 3 wherein the increments are linear and thus inverselyproportional to t1-bandwidth.
 5. The method of claim 3 wherein the TE isincremental from a minimal value to at least 115 ms.
 6. The method ofclaim 1 further comprising providing signal separation for Glu andGlu+Gln.
 7. The method of claim 6 further comprising subtracting a Glusignal acquired from a Glu+Gln signal acquired to provide a measurementof Gln within the single selected data acquisition session foremployment to reconstruct an MR image.
 8. The method of claim 1 furthercomprising detecting spatial distribution for a specified therapy:reconstructing an image of molecular structure for the specifiedtherapy; and adjusting a dose for the specified therapy based on theimage reconstructed.
 9. The method of claim 1 wherein the number of dataacquisition points ranges from approximately 7 to 128 and wherein the TEis incremented beginning at approximately 30 ms.
 10. The method of claim1 further comprising applying a double spin echo acquisition sequencefor volume selection.
 11. The method of claim 1 further comprisingcalculating absolute tissue signal levels of metabolites.
 12. The methodof claim 1 wherein the step of averaging the data acquired comprises:averaging the data acquired within the single selected data acquisitionsession based on a number of the plurality of different TEs of differentlengths employed within the single selected data acquisition session tocause a reduction in signal overlap of target metabolites forreconstruction of an MR image.
 13. The method of claim 12 wherein thestep of detecting the spatial distribution comprises: detecting thespatial distribution of metabolite signals to segregate targetmetabolite signals for clinical analysis through employment of thereduction in signal overlap of the target metabolites from the averageddata based on the number of the plurality of different TEs of differentlengths employed within the single selected data acquisition session tocause the reduction in signal overlap of target metabolites forreconstruction of the MR image.
 14. The method of claim 1 furthercomprising directly measuring glutamate (Glu) and glutamine (Gln) inhuman brain spectroscopy through employment of the spatial distributionof metabolite signals within the single selected data acquisitionsession for employment to reconstruct an MR image.
 15. An apparatus toacquire MR spectroscopy images having metabolite distinction comprising:a magnetic resonance imaging (MRI) system having a plurality of gradientcoils positioned about a bore of a magnet to impress a polarizingmagnetic field and an RF transceiver system and an RF switch controlledby a pulse module to transmit RF signals to an RF coil assembly toacquire MR images; and a computer programmed to: receive an inputindicative of a desired number of acquisition frames within a singleselected data acquisition session; receive an input indicative of adesired span of echo time (TE) for a first acquisition frame dimensionwithin the single selected data acquisition session; calculate avariance from the desired TE for a second acquisition frame within thesingle selected data acquisition session; and apply a pulse sequencewith differing TEs to acquire at least a first and a second acquisitionframe of data within the single selected data acquisition session andreconstruct an image with improved metabolite signal separation.
 16. Theapparatus of claim 15 further comprising a phantom having therein anequivalent mixture of at least two of: Glu, Gln, NAA, Choline, Creatine,myo-Inositol, and GABA.
 17. The apparatus of claim 15 wherein the magnetis capable of producing a magnetic field of at least 3 Tesla, and thecomputer is further programmed to resolve glutamate signals at 2.35 ppmfrom glutamine, N-acetylaspartate, and co-resonant compound signals. 18.The apparatus of claim 15 wherein the computer is further programmed toemploy a variance from the desired TE for a third acquisition frame thatis fixed across the third acquisition frame within the single selecteddata acquisition session.
 19. The apparatus of claim 15 wherein thecomputer is further programmed to acquire TE averaged spin echo data,wherein each spin echo time is varied in duration such that variousmetabolite signals can be segregated in the reconstructed image.
 20. Theapparatus of claim 19 wherein the variance in duration of each spin TEis a fixed increment from one TE to a next and data acquired is averagedover the span of TE.
 21. The apparatus of claim 15 wherein the computeris further programmed to apply an FFT and extract a zero-frequencyspectrum to calculate an average in echo times.
 22. The apparatus ofclaim 15 wherein the computer is further programmed to initiallydetermine T₂ relaxation and estimate metabolite signal at TE=0, and usestandard phantom acquisition data to provide metabolite levelsindependent of T₂ variability in a subject.
 23. The apparatus of claim15 wherein the variance is a fixed increment and TEs range fromapproximately 30 ms. through 115 ms.
 24. A computer readable storagemedium having stored thereon a computer program representing a set ofinstructions that when executed by a computer causes the computer to:apply a pulse sequence having a plurality of data acquisition echo times(TEs) that are averaged over an acquisition period within a singleselected data acquisition session preparatory to reconstruction of an MRimage, wherein at least three of the TEs differ in duration; andreconstruct the MR image having distinction between various metabolitesignals.
 25. The computer readable storage medium of claim 24 whereinthe reconstructed MR image resolves co-resonant signals of glutamate andglutamine from myo-Inositol signals and other co-resonant signals. 26.The computer readable storage medium of claim 24 wherein thereconstructed MR image resolves N-acetyl resonances from confoundingglutamate signals.
 27. The computer program of claim 24 having furtherinstructions to cause the computer to phase correct each frame of TEdata with a residual water signal.
 28. The computer program of claim 24having further instructions to cause the computer to obtain a waterreference point and correct any frequency and phase errors using thewater reference point obtained.
 29. The computer program of claim 24having further instructions to cause the computer to calculate anabsolute tissue level of a plurality of metabolite signals from thereconstructed image.